Abstract
With the emergence of resource powerful sensor nodes, the concept of WSN virtualization is gaining increasing attention from the research community and the industry. One approach to achieve WSN virtualization is to exploit the capabilities of individual sensor nodes to execute tasks of multiple applications concurrently. In this paper, we consider the problem of task allocation in software-defined WSNs (SD-WSNs), which are distinguished by centralized control plane and programmable data plane. We extend our previous work on this topic, where we proposed the control algorithm which determines suitability of a sensor node for task allocation based on the active routing paths and residual energy in the network. Availability of such information can be easily justified in SD-WSNs. Through extensive simulations, the performance of this strategy has been evaluated and compared with two conventional task allocation approaches, which assume traditional minimum-hop routing. In addition, we analysed performance of more simple software defined networking-based approach, which performs resource allocation by considering only residual energy in the network. The obtained results demonstrate benefits of SD-WSN architecture when it comes to virtualization efficiency, and clarify improvements achieved by mutual correlation of routing and task allocation decisions.
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Khan, I., Belqasmi, R., Glitho, R., Crespi, N., Morrow, M., & Polakos, P. (2016). Wireless sensor network virtualization: A survey. IEEE Communications Surveys & Tutorials, 18(1), 553–576.
Arampatzis, T., Lygeros, J., & Manesis, S. (2005). A survey on applications of wireless sensors and wireless sensor networks. In Proceedings of IEEE Mediterrean conference on control and automation (pp. 719–724).
Li, W., Delicato, F. C., Pires, P. F., & Pirmez, L. (2014). Efficient allocation of resources in multiple heterogeneous wireless sensor networks. Journal of Parallel Distributed Computing, 74(1), 1775–1788.
Khan, I., Belqasmi, F., Glitho, R., & Crespi, N. (2013). A multi-layer architecture for wireless sensor network virtualization. In Proceeding of 6th joint IFIP wireless and mobile networking conference (WMNC) (pp. 1–4).
Khan, I., Belqasmi, F., Glitho, R., Crespi, N., Morrow, M., & Polakos, P. (2015). Wireless sensor network virtualization: Early architecture and research perspectives. IEEE Network, 29(3), 104–112.
Sarakis, L., Zahariadis, T., Leligou, H.-C., & Dohler, M. (2012). A framework for service provisioning in virtual sensor networks. EURASIP Journal on Wireless Communications and Networking, 1(1), 1–19.
Merentitis, A. et al. (2013). WSN trends: Sensor infrastructure virtualization as a driver towards the evolution of the internet of things. In Proceeding of 7th international conference on mobile ubiquitous computing, systems, services and technologies (pp. 113–118).
Ramdhany, R., & Coulson, G. (2013). Towards the coexistence of divergent applications on smart city sensing infrastructure. In Proceeding of 4th international workshop on networks of cooperating objects for smart cities (pp. 26–30).
Islam, M. M., & Huh, E.-N. (2012). Virtualization in wireless sensor network: Challenges and opportunities. Journal of Networks, 7(3), 412–419.
Yu, Y., Rittle, L. J., Bhandari, V., & Le Brun, J. B. (2006). Supporting concurrent applications in wireless sensor networks. In Proceeding of the 4th international conference on embedded networked sensor systems (pp. 139–152).
Monali, G.-S., & Nikam, S. (2014). Efficient resource utilization through sensor virtualization. International Journal of Computer Science and Information Technologies, 5(1), 699–703.
Tomovic, S., & Radusinovic, I. (2016). Allocation algorithm for handling multiple applications in software-defined WSN. In Proceeding of 24th telecommunications forum (TELFOR) (pp. 1–4).
Farias, C. M., et. al. (2013). A scheduling algorithm for shared sensor and actuator networks. In Proceeding of the international conference on information networking (ICOIN) (pp. 648–653).
Zeng, D., Li, P., Guo, S., Miyazaki, T., Hu, J., & Xiang, Y. (2014). Energy minimization in multi-task software-defined sensor networks. IEEE Transactions on Computers, 64(11), 3128–3139.
Thippeswamy, B. M., et al. (2014). EDOCR: Energy density on-demand cluster routing in wireless sensor networks. International Journal of Computer Networks & Communications, 6(1), 223–241.
Tomovic, S. & Radusinovic, I. (2015). Performance analysis of a new SDN-based WSN architecture. In Proceeding of 23rd telecommunication forum TELFOR (pp. 99–102).
Costanzo, S., Galluccio, L., Morabito, G., & Palazzo, S. (2012). Software defined wireless networks: Unbridling SDNs. In European workshop on software defined networking (pp. 16–24).
Tomovic, S., Pejanovic-Djurisic, M., & Radusinovic, I. (2014). SDN-based mobile networks: Concepts and benefits. Wireless Personal Communications, 78(3), 1629–1644.
Tomovic, S., Yoshigoe, K., Maljevic, I., & Radusinovic, I. (2017). Software-defined fog network architecture for IoT. Wireless Personal Communications, 92(1), 181–196.
Dunkels, A., Bjorn, G., & Thiemo, V. (2004). Contiki—a lightweight and flexible operating system for tiny networked sensors. In Proceeding of 29th annual IEEE international conference on local computer networks (pp. 455–462).
Levis, P., et al. (2005). TinyOS: An operating system for sensor networks. In W. Weber, J. M. Rabaey, & E. Aarts (Eds.), Ambient Intelligence (pp. 115–148). doi:10.1007/3-540-27139-2_7.
Baccelli, E., et al. (2013). RIOT OS: Towards an OS for the internet of things. In 32nd IEEE INFOCOM, Poster.
Get Started with SDN-WISE. http://sdn-wise.dieei.unict.it/docs/guides/GetStarted.html. Accessed 30 July 2016.
De Oliveira, B. T., Margi, C. B., & Gabriel, L. B. (2015). TinySDN: Enabling multiple controllers for software-defined wireless sensor networks. IEEE Latin America Transactions, 1(13), 3690–3696.
EMB-Z2530PA datasheet. (2017). http://www.embit.eu/products/wireless-modules/emb-z2530pa.
MEMSIC TelosB Datasheet. (2011). http://www.memsic.com/userfiles/files/DataSheets/WSN/telosb_datasheet.pdf.
Levis, P. & Culler, D. (2002). Mat: A tiny virtual machine for sensor networks. In ASPLOSX: Proceedings of the 10th international conference on architectural support for programming languages and operating systems (pp. 85–95).
Gupta, V., et al. (2011). Nano-CF: A coordination framework for macro-programming in wireless sensor networks. In Proceedings of 8th annual IEEE communications society conference on sensor, mesh and Ad Hoc communications and networks (SECON), pp. 467–475.
Koshy, J., & Pandey, R. (2005). VMSTAR: Synthesizing scalable runtime environments for sensor networks. In Proceedings of the 3rd international conference on embedded networked sensor systems (pp. 243–254).
Fok, C.-L., Roman, G.-C., & Lu, C. (2006). Agila: A mobile agent middleware for delf-adaptive wireless sensor networks. ACM Transactions on Autonomous Adaptive Systems, 4(3), 1–26.
Simon, D. et al. (2006). Java on the bare metal of wireless sensor devices: The Squawk Java virtual machine. In Proceedings of the 2nd international conference on virtual execution environments (pp. 78–88).
Bandara, H. M. N. D., Jayasumana, A. P., & Illangasekare, T. H. (2008). Cluster tree based self organization of virtual sensor networks. In IEEE GLOBECOM workshops (pp. 1–6).
Buratti, C., et al. (2016). Testing protocols for the internet of things on the EuWIn platform. IEEE Internet of Things Journal, 3(1), 124–133.
Qun, Z., & Gurusamy, M. (2006). Maximizing network lifetime for connected target coverage in wireless sensor networks. In Proceedings of IEEE international conference on wireless and mobile computing (pp. 94–101).
Heinzelman, W. B., Chandrakasan, A. P., & Balakrishnan, H. (2002). An application-specific protocol architecture for wireless microsensor networks. IEEE Transaction on Wireless Communications, 1(4), 660–670.
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This work has been supported by the BIO-ICT Centre of Excellence (Contract No. 01-1001) funded by Ministry of Science of Montenegro and the HERIC project.
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Tomovic, S., Radusinovic, I. Mapping Application Requirements to Virtualization-Enabled Software Defined WSN. Wireless Pers Commun 97, 1693–1709 (2017). https://doi.org/10.1007/s11277-017-4650-0
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DOI: https://doi.org/10.1007/s11277-017-4650-0